Climate response to projected changes in short-lived species under an A1B...

Shindell, D., G. Faluvegi, S. E. Bauer, D. Koch, N. Unger, S. Menon, R. L. Miller, G. A. Schmidt, and D. Streets (2007), Climate response to projected changes in short-lived species under an A1B scenario from 2000–2050 in the GISS climate model, J. Geophys. Res., 112, D20103, doi:10.1029/2007JD008753.
Abstract: 

We investigate the climate forcing from and response to projected changes in shortlived species and methane under an A1B scenario from 2000-2050 in the GISS climate model. We present a meta-analysis of new simulations of the full evolution of gas and aerosol species and other existing experiments with variations of the same model. The comparison highlights the importance of several physical processes in determining radiative forcing, especially the effect of climate change on stratosphere-troposphere exchange, heterogeneous sulfate-nitrate-dust chemistry, and changes in methane oxidation and natural emissions. However, the impact of these fairly uncertain physical effects is substantially less than the difference between alternative emission scenarios for all short-lived species. The net global mean annual average direct radiative forcing from the short-lived species is .02 W/m2 or less in our projections, as substantial positive ozone forcing is largely offset by negative aerosol direct forcing. Since aerosol reductions also lead to a reduced indirect effect, the global mean surface temperature warms by $0.07°C by 2030 and $0.13°C by 2050, adding 19% and 17%, respectively, to the warming induced by long-lived greenhouse gases. Regional direct forcings are large, up to 3.8 W/m2. The ensemble-mean climate response shows little regional correlation with the spatial pattern of the forcing, however, suggesting that oceanic and atmospheric mixing generally overwhelms the effect of even large localized forcings. Exceptions are the polar regions, where ozone and aerosols may induce substantial seasonal climate changes.

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Research Program: 
Atmospheric Composition Modeling and Analysis Program (ACMAP)
Modeling Analysis and Prediction Program (MAP)